The invention relates generally to electrocardiograms (ECGs) and the use thereof, and more particularly to, a method and apparatus to detect acute cardiac syndromes that is specific with respect to gender, age, height, weight, and/or race.
ECG analysis is a well established method for studying the function of the heart and identifying disorders of the heart. ECG is an important tool in diagnosing patients presented to an emergency room with chest pain. One particular disorder that is studied using ECG is acute cardiac syndromes (ACS), which includes, but is not limited to, acute myocardial infarction (MI) and acute cardiac ischemia (ACI), the latter of which is commonly referred to as unstable angina. Acute ischemia includes the starvation of oxygen to a portion of the heart, commonly caused by a partial blockage of the coronary arteries providing oxygenated blood to the heart, and acute infarction is due to the complete blockage of oxygen to a portion of the heart. Ischemia, or unstable angina, can lead to or be a symptom of infarction. It is well known that time is critical in diagnosing these conditions in a patient experiencing chest pain. Delay in diagnosis and therapy can result in serious impairment of the heart""s function, including sudden death.
An ECG is a graphic tracing of the variations in the electrical potential caused by the excitation of the heart muscle and is detected at the body surface by an ECG device. The typical ECG is a scale or representation that shows deflections resulting from cardiac activity as changes in the magnitude of voltage and polarity over time and includes a P-Wave, a QRS complex, a T-Wave, and a U-Wave. These waves are then analyzed using a set of rules and parameters to determine what is normal and what is not. Certain deviations are used to flag a possible ACS.
However, recent studies indicate a significant difference in these xe2x80x9ctypicalxe2x80x9d clinical profiles, presentations, and outcomes between men and women with ACS that were not attributable to differences in baseline characteristics. Studies have shown that younger women have a higher mortality than older women, and men of all ages, following myocardial infarction. However, to date, these studies have not conclusively shown direct evidence that the findings might be attributed to pathophysiological and/or anatomical differences between men and women. For example, electrocardiographic evidence of acute MI conventionally includes the presence of ST elevations of at least 100 xcexcV in two anatomically contiguous leads (a higher threshold of 200 xcexcV is used for precordial leads). Since the previous studies used conventional, clinical criteria to assess the presence of acute MI and thereby determine the course of care for the patients, it is believed that the differences in mortality rates may be attributed, at least partially, to sub-clinical differences in the ST elevation levels on the admission ECG. If present, the sub-clinical differences in ST levels between symptomatic male and female patients (e.g., those complaining of chest pain) may be revealed only through more accurate computerized measurements of the ST levels from signal averaged (median) data. It is believed that these differences may have been obscured by the fact that development of conventional criteria for ECG ACS evidence was carried out through manual ST measurements on a baseline group that was largely male dominated or undifferentiated by gender, age, height, weight and race.
There are a number of computerized ECG analysis systems in the marketplace. However, it is generally believed that they all rely on a baseline group of patients that provides criteria that may be biased against certain groups of patients. It would therefore be advantageous to optimize the performance of computerized ACS criteria to more accurately detect such acute cardiac syndromes as acute MI and ACI for a patient falling within one group that does not necessarily have the same characteristics of the baseline group. For example, it is proposed herein that female patients under the age of 60 should have a lower ST elevation threshold than the male dominated group used as the traditional baseline. Therefore, it would be advantageous to improve the sensitivity for detection of acute MI/ACI for female patients while maintaining high specificity and, thus, eliminate the bias in the current criteria used.
A method and apparatus is disclosed to improve detection of acute cardiac syndromes (ACS) in specified groups of patients using ECG analysis to eliminate bias introduced by the current criteria that solves the aforementioned problems.
The invention includes the development and implementation of a computerized ACS criteria based analysis system to optimize performance for specified groups of patients. To develop the new criteria, a database of patient records is examined in which the patient records confirm the existence of ACS or the absence of ACS. That is, to ensure a bias neutral study, the presence or absence of ACS must be confirmed by a non-ECG diagnosis. For gender-based criteria, the database of admission ECGs divided into female and male groups. The difference of at least one ECG parameter is examined between the groups. In this example, the ECG parameter tested is the ST segment measurement of the ECG waveform. Either a fuzzy logic or a neural network can be used for pattern recognition in addition to classical pattern recognition methods such as linear discriminant function analysis and thresholding. After the differences are examined, a significance is assigned to the difference. Based on the significance assigned, the ECG-based automatic detection of ACS can be optimized for the specified subgroup.
In accordance with one aspect of the invention, a method of developing automatic detection of ACS using ECG signals includes examining a difference of at least one ECG parameter from patients in a baseline group that includes patients having ACS and those not having ACS, with patients in a second group that includes patients, also, having ACS and those not having ACS. After determining a significance of the differences examined, the method includes optimizing performance of ECG-based automatic detection of ACS for the second group of patients based on the significance determined. In a preferred embodiment, the ECG parameter is ST elevation. Since it has been found herein that female patients have a lower critical ST elevation than the baseline, male dominated group, the invention includes lowering the threshold level of the ST elevation parameter in the ECG analysis.
In accordance with another aspect of the invention, an ECG analysis program is disclosed which, when executed, causes a processor to acquire ECG data from a patient, determine whether the patient is in one of a prespecified group, and if so, applies analysis criteria specific for the prespecified group to identify if the patient has an ACS. If the patient is not in a prespecified group, the program applies known analysis criteria to the ECG data. The group is specified based on gender, age, race, weight, height, or a combination thereof. The analysis includes modifying various parameters based on the specific group selected.
In accordance with another aspect of the invention, a method and apparatus, that includes an ECG device, is disclosed. The method is a criterion based, group membership-specific ACS detection method. The method includes specifying a group membership designated as having differing ECG data as compared to a baseline group, acquiring ECG data from a patient experiencing ACS symptoms, and then analyzing the ECG data based on group membership. The steps of the method are programmed into a processing unit of an ECG device having a plurality of lead wires to acquire the ECG data from the patient.
In a preferred embodiment, the specified group is females under the age of 60 and the ECG data includes lowering the ST segment, checking ST depression level in reciprocal leads and T wave thresholds so as to more accurately identify acute anterior myocardial infarction (MI) and acute inferior MI in younger females. This gender and age specific ACS criteria improve the sensitivity while maintaining high specificity and overall accuracy of acute ACS detection for female patients, especially those under the age of 60.
Various other features, objects and advantages of the present invention will be made apparent from the following detailed description and the drawings.